Using Digital Tools To Enhance Finance Agility

In times of great uncertainty, one of the most effective qualities of the finance organization is agility. Agility means being able to sync up the pace of internal change with that of the external environment. Facing today’s political, economic, and financial market unpredictability, the onus is on finance to turbocharge its agility. The Hackett Group benchmarks show that top-performing agile companies are four times more likely to improve cost under volatile business conditions. They are three times more likely to make important decisions quickly, and twice as likely to respond quickly to change in business demands or conditions. In short, it pays to be agile.

Putting agility on digital “steroids”

Agility in its traditional sense is no longer enough, however. Its purpose is to help finance keep pace with external change. However, to be successful today, finance needs to be able to anticipate change and come up with contingency plans for multiple scenarios. It can accelerate its internal adaptability by adopting digital technologies. By enhancing planning techniques and processes with the powers of Big Data, advanced analytics, robotic process automation (RPA), and cloud tools, finance can spot trouble faster, predict future developments, and help companies quickly adjust course.

Here are four ways digital solutions can help:

Use sophisticated models to run multiple scenario analyses. Advanced analytics models can help finance run scenario analyses using different inputs and ask probing questions. There are too many what-ifs for the human mind to contain, especially because they are all interdependent. Using predictive models can help finance quickly run through multiple scenarios, get them to interplay, and come up with possible outcomes.

Augment finance GBS with RPA. A big part of agility is removing inefficiencies and getting the right talent doing the right things. If finance is bogged down inputting data or reconciling invoices, it won’t have a chance to help foresee events or come up with mitigation plans. New technologies like RPA are providing opportunities for quick returns that can also get around any backlash against labor arbitrage.

Leverage Big Data. Internal numerical data is not going to feed sophisticated, multidimensional models. To keep a finger on the market pulse, finance needs to start pulling real-time and leading indicator data from external sources, including social media feeds. While full Big Data capability may take time to develop, some finance organizations are already running pilot programs applying Big Data techniques to solve specific business issues.

Shift to agile planning techniques. Finally, new cloud-based, end-to-end enterprise performance management (EPM) solutions are speeding up the adoption time for EPM systems. They’re also reducing the cost of ownership, making it possible even for midsize firms to adopt dynamic planning techniques. They can then use the forecast to continuously reallocate resources to optimize returns based on shifting market realities and take a forward-looking approach to planning.

Still, finance must move even faster, to meet the increasingly risky and volatile business environment of today. The onus is on finance to take quick steps to come up the learning curve. The three most critical steps include:

Create a digital strategy. Finance needs to come up with coherent strategy that’s aligned with the organization’s digital transformation objectives. If the company is looking to enhance customer experience though better utilization of social media, finance needs to define how it’s going to support its internal customers and what technologies it needs to be able to deliver on the overall strategic objective.

Change the operating model. Finance needs to build the right operating model to turbocharge the agility of the function with digital technologies. It needs to pull together its best talent and place them in a centralized location to create a powerful analytics hub. A Center of Excellence can offer streamlined analytics and decision support and focus on areas where Big Data and analytics can provide real business value. It can also simplify the interaction model with business leaders and management.

Train and hire new tech- and analytic-savvy professionals. Finally, finance needs to build up its digital capabilities by preparing its talent for change more quickly. Simply adopting new tools won’t get the organization to its optimal state. The skills and capabilities needed to support an uber-analytics function include intellectual curiosity, familiarity with the right technologies, and strong communication skills. Finance professionals also have to be comfortable with ambivalence: Often they will need to provide insight without 100% of the information. And they need to understand the business to be able to quickly grasp what external changes may affect the company’s performance.

Conclusion

Companies today face multiple risks and a higher level of uncertainty. Geopolitical indicators are pointing to a period of extreme unpredictability, which may lead to financial instability and both opportunities and challenges for enterprise growth. Against this backdrop, finance needs to accelerate its ability to react. It must incorporate new tools into its toolkit so it can foresee upcoming events and develop contingency plans through the adoption of new technologies like artificial intelligence, cloud-based solutions, and predictive modelling.